Computational Semantics and Pragmatics Autumn 2011 Raquel Fernández Institute for Logic, Language & Computation University of Amsterdam Raquel Fernández COSP 2011 1 / 32
What is this course about? About the semantics and pragmatics of natural language — about meaning and interpretation in context, and about language use in interaction. Some general key questions we will address are: • how can we model the meaning of words? • what kind of inferences can we draw from sentences or discourses? • how do we use and interpret language in dialogue? The course is also about using computational and empirical methods to explore semantic/pragmatic phenomena • computational resources such as linguistic corpora and databases • algorithms and automatic tools Raquel Fernández COSP 2011 2 / 32
Related Courses • This is a new course at the interface of the Logic & Language and the Language & Computation groups at the ILLC. • (Mildly) related courses within the MoL: ∗ Structures for Semantics ( Maria Aloni / Robert van Rooij ) ∗ Meaning, Reference and Modality ( Paul Dekker ) ∗ Inquisitive Semantics ( Jeroen Groenendijk / Floris Roelofsen ) ∗ Language and Optimality ( Reinhard Blutner / Henk Zeevat ) ∗ Mechanisms of Meaning ( Henk Zeevat ) ∗ Elements of Language Processing and Learning ( Khalil Sima’an ) ∗ Cognitive Models of Language and Beyond ( Rens Bod ) Raquel Fernández COSP 2011 3 / 32
Prerequisites No formal prerequisites are required to follow the course. However, some basic things are expected from you: • an interest in natural language, particularly in semantics/ pragmatics - in meaning, interpretation, and interaction. • an empirical orientation: an interest in the empirical evidence (or lack thereof) behind theoretical claims; and in working with data. • a computational inclination: an interest in computational methods of enquiry and evaluation ∗ does this mean you need to know how to program? No! but if you do, then you’ll have the chance to use your programming skills. ⇒ Please fill in the student questionnaire on the website to let me know about your background and interests. Raquel Fernández COSP 2011 4 / 32
Practical Matters • Lecturer: Raquel Fernández, <raquel.fernandez@uva.nl> • Website: Slides, references, and other important information will be posted on the course’s website: http://www.illc.uva.nl/~raquel/teaching/cosp2011/ • Timetable: Thursday 15-17 in D1.168 till 27 Oct, then G2.04 ∗ no class in the following two weeks; need to find a different slot in the week of 26 Sept. [ we’ll discuss this later ] • Seminars: There may be talks at the ILLC that are relevant to the course and that you are welcome/encouraged to attend: ∗ Computational Linguistics Seminar (CLS) ∗ DIP (discourse processing) Colloquium Check the ILLC Events webpage for details. Raquel Fernández COSP 2011 5 / 32
Evaluation • Homework exercises involving any of the following: ∗ analytical thinking ∗ use of online corpora and web interfaces to examine data ∗ running algorithms to obtain results • Reading relevant research papers and presenting or discussing them (to be made more concrete later on) • Individual final paper to be presented at the end of the course ∗ on-topic philosophical/theoretical essays are in principle OK, but ∗ ideally, your project should include an empirical/computational component, e.g. analysis of real data or some sort of implementation Raquel Fernández COSP 2011 6 / 32
Plan for today 1. Overview of the main topics of the course 2. Introduction to Textual Entailment Raquel Fernández COSP 2011 7 / 32
Overview of Course Topics Raquel Fernández COSP 2011 8 / 32
Meaning and Understanding How can we characterise what understanding natural language is? This is a tough question and there are plenty of proposals... • to know the meaning of a (declarative) sentence is to know what the world would have to be like for the sentence to be true • ... to know how it changes the context (by adding knowledge, by making relevant follow-up expressions,etc.) • ... to be able to use an expression appropriately given the conventions of a linguistic community • ... to be able to (re)act according to what is expected ... All these takes on meaning and understanding can be seen as complementary: all possibly necessary but none sufficient. Raquel Fernández COSP 2011 9 / 32
Meaning and Inference Another necessary condition for natural language understanding is the ability to recognise entailment and contradiction. • If you understand these sentences, you can recognise that (1) and (2) are contradictory ... (1) No civilians were killed in the Najaf suicide bombing. (2) Two civilians died in the Najaf suicide bombing. • ... and that if (3) is true then (4) is true as well. (3) Apple filed a lawsuit against Samsung for patent violation. (4) Samsung has been sued by Apple. Recognising whether entailment holds is a core aspect of our ability to understand language. Raquel Fernández COSP 2011 10 / 32
Recognising Textual Entailment Textual Entailment is a notion broader than logical entailment defined by the computational linguistics community as follows: Textual entailment is a relation that holds between a pair � T , H � of natural language expressions (a text and a hypothesis ), such that a human who reads (and trusts) T would infer that H is most likely true. RTE can be seen as an abstract generic ability that captures inferential/semantic capabilities required by many tasks involving understanding. ⇒ How can we model this ability computationally? Challenges include: ∗ characterising the sources of the entailment (syntactic, semantic,...) ∗ background knowledge ∗ ambiguity Raquel Fernández COSP 2011 11 / 32
Lexical Semantics Next, we will move on to lexical semantics (meaning of words). Formal compositional semantics employs a rather crude notion of lexical meaning: [ [ dolphin ] ] = { x | x is a dolphin } f : D → { 1 , 0 } � e , t � [ [ envy ] ] = {� x , y � | x envies y } f : D → ( D → { 1 , 0 } ) � e , � e , t �� How can we model word senses and the relations that hold between them in a more fine-grained manner? • Hyponymy and Hypernymy: relation of semantic inclusion that holds between a more general term such as ‘bird’ and a more specific term such as ‘robin’ • Synonymy: relation of semantic identity between senses, e.g. ‘aurora/dawn/sunrise’ , ‘whore/prostitute’ • Antonymy: relation of semantic oppositeness between senses, e.g. ‘tall/short’ , ‘dead/alive’ • Meronymy: part-whole relation between senses, e.g. ‘elbow/arm’ , ‘keyboard/computer’ Raquel Fernández COSP 2011 12 / 32
Distributional Semantic Models We will focus on Distributional Semantic or Vector Space Models. • These models take a usage-based view of word meaning. • Their basic underlying idea is that word meaning depends on the contexts in which words are used. • An example by Stefan Evert: what’s the meaning of ‘bardiwac’ ? ∗ He handed her her glass of bardiwac. ∗ Beef dishes are made to complement the bardiwacs. ∗ Nigel staggered to his feet, face flushed from too much bardiwac. ∗ Malbec, one of the lesser-known bardiwac grapes, responds well to Australia’s sunshine. ∗ I dined on bread and cheese and this excellent bardiwac. ∗ The drinks were delicious: blood-red bardiwac as well as light, sweet Rhenish. ⇒ ‘bardiwac’ is a heavy red alcoholic beverage made from grapes Raquel Fernández COSP 2011 13 / 32
The Distributional Hypothesis • DH: The degree of semantic similarity between two linguistic expressions A and B is a function of the similarity of the linguistic contexts in which A and B can appear (Harris, 1954) • DSMs make use of mathematical and computational techniques to turn the informal DH into empirically testable semantic models. • They build contextual semantic representations from data about language usage. • These representations are defined as an abstraction over the linguistic contexts in which a word is encountered. ⇒ We will study the philosophical ideas behind these models and the computational techniques currently used to build them. Raquel Fernández COSP 2011 14 / 32
Conversational Implicature Then we’ll move on to more typically pragmatic issues... Entailments are not the only inferences we are able to make when we understand language in context: A: Which room is the seminar in next week? B: It’s in the G building. � A does not know in which room the seminar is. A: Where can I get gas around here? B: There is a garage around the corner. � A can get gas at a garage around the corner. According to the philosopher Paul Grice, we are able to make inferences like the ones above, called conversational implicatures, because we follow general principles of cooperation. The Cooperative Principle: Make your contribution such as it is required, at the stage at which it occurs, by the accepted purpose or direction of the talk exchange in which you are engaged. (Grice 1975) Raquel Fernández COSP 2011 15 / 32
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